Exploring robust methods for evaluating treatment and comparison groups in chronic care management programs. Temporarily coarsen each control variable in x as much as you are willing, for the purposes of matching. The % cem macro integrates the already available software alternatives introducing a completely automated coarsened exact matching macro for sas users. Comparing the matching properties of coarsened exact matching, propensity score matching, and genetic matching in a nationwide observational data and a monte carlo experiment by shanshan qin ba, renmin university of china, 2007 a thesis submitted to the graduate faculty of the university of georgia in partial fulfillment. Coarsened exact matching cem is a relatively new causal inference technique that allows the researcher to nonparametrically create a matched dataset to evaluate the effect of a treatment. This algorithm, and its statistical properties, are described in iacus, king, and porro 2008. A new technique for statistical matching presentation by martin ehlert and jan paul heisig wzb at the co. Im not aware of any research comparing cem with more recent methodologies. The cem command implements the coarsened exact matching algorithm in stata.
We used coarsened exact matching to generate a distribution of likely causes of death for each death certified to heart failure. Cem is a package for r, stata, and spss that implements the method of coarsened exact matching. Exact sequences for the homology of the matching complex. Covariate selection and coarsened exact matching in causal. Cem improves causal inferences and reduces model dependence by making observations more comparable. I could not understand however whether this option actually requires an exact matching on that variable. We discuss a method for improving causal inferences called coarsened exact matching cem, and the new. Coarsened exact matching coarsened exact matching cem is a monotonoic imbalance bounding mib matching method which means that the balance between the treated and control groups is chosen by the user ex ante rather than discovered through the usual laborious process of checking after the fact and repeatedly reestimating, and so that adjusting the imbalance on one variable has no effect on the. Iacus, gary king, and giuseppe porro, causal inference without balance checking. Matching is a nonparametric method of preprocessing data to control for some or all of the potentially confounding influence of pretreatment control variables by reducing imbalance between. For example, years of education might be coarsened into grade school, middle school, high school, college, graduate school. Gary king of harvard university offers a different take on matching procedures by means of a new technique known as coarsened exact matching cem.
Coarsened exact matching and multivariate matching methods that are monotonic imbalance bounding. Iacus, gary king, and giuseppe porro, matching for causal inference without balance checking. Other types of matching such as the matching estimator nnmatch have an exact option which tells the program that on certain variables the match must be precise. Exploring robust methods for evaluating treatment and. Overview this program is designed to improve causal inference via a method of matching that is widely applicable in observational data and easy to understand and use if you understand how to draw a histogram, you will understand this method. Coarsened exact matching more info with stefano iacus, giuseppe porro and gary king. The program implements thecoarsened exact matching cem algorithm, described below. Stefano iacus, gary king, giuseppe porro this program is designed to improve the estimation of causal effects via an extremely powerful method of matching that is widely applicable and exceptionally easy to understand and use if you understand how to draw a histogram, you will understand this method. Iacus, gary king, giuseppe porro skip to main content accessibility help we use cookies to distinguish you from other users and to provide you with a better experience on our websites. This program is designed to improve causal inference via a method of matching that is widely applicable in observational data and easy to understand and use if you understand how to draw a histogram, you will understand this method. Coarsened exact matching is faster, is easier to use and understand, requires fewer assumptions, is more easily automated, and possesses more attractive statistical properties for many applications than do existing matching methods.
Multivariate and propensity score matching software with. Both the matching strategy including some standard coarsening options and the associated l1 multivariate imbalance measure are provided. A member with an age bin value of 1, can only match a member in the other cohort with the exact same value of 1. Cem algorithm performs exact matching on coarsened data to determine matches and then passes on the uncoarsened data from observ ations that were matched to estimate the causal e. Algorithm the cem algorithm then involves three steps. Cem may be used alone or in combination with any existing matching method. Coarsened exact matching for stata matthew blackwell institute for quantitative social science harvard university joint work with stefano m. Cem via the dialog menu in order to demonstrate the syntax of cem in spss, you can download an example dataset of a job training program. Using sas software to perform a casecontrol match on propensity score in an. In coarsened exact matching, users temporarily coarsen their data, exact match on these coarsened data, and then.
Coarsened exact matching is a powerful algorithm but simple to use. Coarsened exact matching cem on panel data statalist. Its 2018 tutorial on automating educational research. The need for rigorous impact evaluation of global health programs has become paramount in a changed funding environment that demands accountability and measurable results. Multivariate and propensity score matching software with automated balance optimization. This algorithm, and its statisticalproperties, are described in iacus, king, and porro 2008. Two roads diverged in a narrow datasetwhen coarsened. Sekhon uc berkeley abstract matching is an r package which provides functions for multivariate and propensity score matching and for nding optimal covariate balance based on a genetic search algorithm. Cem authors originally provided few software solutions for standard softwares like r, stata and spss to perform their algorithm. Matching is a nonparametric method of preprocessing data to control for some or all of the potentially confounding influence of pretreatment control variables by reducing imbalance between the treated and control groups.
Sta colloquium as empirical tests of causal claims derived from theories become more important in the social sciences, researchers who rely on observational data are confronted with with the inadequacy of. Other matching methods inherit many of the coarsened exact matching methods properties when applied to further match data preprocessed by coarsened exact matching. Methods and application for evaluating global health programs. Reducing bias in a propensity score matchedpair sample using greedy matching techniques. This algorithm, and its statistical properties, are described in stefano m. Propensity score matching psm is the older, more established technique in the literature. Software for coarsened exact matching, journal journal of statistical software, year 2009 share. Cem may be used alone or in combination with any existing. Is it the case that if i give cem the cutoff points the match is strict. Each matched member must have the exact same bin as their matched cohort. Coarsened exact matching in stata matthew blackwell. The program implements the coarsened exact matching cem algorithm, described below. Cem may be used aloneor in combination with any existing matching method. Coarsened exact matching volume 20 issue 1 stefano m.